Analyst II, Full Stack

2-4 years work experience in customer risk management at a payments or financial company. Fluent in SQL and Python. Ability to collaborate and influence across different teams. Ability to clearly communicate findings and recommendations to technical and non-technical audiences. Passion to understand product workings and how to improve them. Strong time management skills and ability to manage multiple projects. Ability to thrive in a fast-paced environment. Bachelor's or Master's degree in engineering, statistics, math, or economics is desired. Knowledge of payment processing fundamentals and industry risk trends.

Explore data to identify opportunities for product development and improvement in Trust and Safety. Drive analytical work for online experiments to optimize strategies and improve conversion rates. Translate analysis into recommendations for business logic to enhance identity and fraud conversion or fraud rates. Develop scalable frameworks for managing tiered cutoffs for fraud machine learning models. Evaluate new data sources for fraud risk and partner with data engineering on data pipelines. Own end-to-end analytics workflow, including defining metrics, socializing them, and creating dashboards and reports. Partner with Machine Learning on building fraud and identity verification strategies for new products, markets, and user segments. Collaborate with Product and Engineering to identify high-impact points in the funnel for user acquisition and retention.